Augmented COVID-19 CT images with CUTMIX, CUTOUT, and MIXUP Data Augmentation

This dataset consists of 30,000 augmented COVID-19 CT images generated from CUTMIX (Yun et al., 2019), CUTOUT (DeVries & Taylor, 2017), and MIXUP (Zhang et al., 2018) data augmentation techniques. The COVID-19 CT images are acquired from multiple publicly available sources (Morozov et al., 2020; Rahimzadeh et al., 2021; Maftouni et al., 2021).

References
DeVries, T., & Taylor, G. W. (2017). Improved regularization of convolutional neural networks with cutout. arXiv preprint arXiv:1708.04552

Maftouni, M., Law, A.C, Shen, B., Zhou, Y., Yazdi, N., & Kong, Z.J. (2021). A Robust Ensemble-Deep Learning Model for COVID-19 Diagnosis based on an Integrated CT Scan Images Database. In Proceedings of the 2021 Industrial and Systems Engineering Conference (pp. 632-637). Institute of Industrial and Systems Engineers.

Morozov, P., Andreychenko, A. E., et al. (2020). MosMedData: Chest CT Scans With COVID19 Related Findings Dataset. arXiv preprint arXiv: 2005.06465.

Rahimzadeh, M., Attar, A., & Sakhaei S. (2021). A fully automated deep learning-based network for detecting COVID-19 from a new and large lung CT scan dataset. Biomedical Signal Processing and Control, 68, pp. 102588.

Yun, S., Han, D., Oh, S. J., Chun, S., Choe, J., & Yoo, Y. (2019). CutMix: Regularization strategy to train strong classifiers with localizable features. arXiv preprint arXiv:1905.04899

Zhang, H., Cisse, M., Dauphin, Y. N., & Lopez-Paz, D. (2018). Mixup: Beyond empirical risk minimization. arXiv preprint arXiv:1710.09412

本数据集包含30000张经数据增强（data augmentation）处理的COVID-19 CT影像，这些影像通过CUTMIX（Yun等，2019）、CUTOUT（DeVries与Taylor，2017）以及MIXUP（Zhang等，2018）三种数据增强技术生成。该COVID-19 CT影像源自多个公开数据源（Morozov等，2020；Rahimzadeh等，2021；Maftouni等，2021）。

参考文献
DeVries, T., & Taylor, G. W. (2017). 基于Cutout的卷积神经网络正则化改进. arXiv预印本，arXiv:1708.04552
Maftouni, M., Law, A.C, Shen, B., Zhou, Y., Yazdi, N., & Kong, Z.J. (2021). 基于集成CT扫描影像数据库的新型冠状病毒肺炎（COVID-19）诊断鲁棒集成深度学习模型. 见2021年工业与系统工程会议论文集（第632-637页）. 工业与系统工程师协会
Morozov, P., Andreychenko, A. E., et al. (2020). MosMedData：带有新型冠状病毒肺炎（COVID-19）相关影像学表现的胸部CT扫描数据集. arXiv预印本，arXiv: 2005.06465.
Rahimzadeh, M., Attar, A., & Sakhaei S. (2021). 基于全新大规模肺部CT扫描数据集的全自动深度学习网络用于新型冠状病毒肺炎（COVID-19）检测. 生物医学信号处理与控制, 68, 第102588页.
Yun, S., Han, D., Oh, S. J., Chun, S., Choe, J., & Yoo, Y. (2019). CutMix：训练具备可定位特征的强分类器的正则化策略. arXiv预印本，arXiv:1905.04899
Zhang, H., Cisse, M., Dauphin, Y. N., & Lopez-Paz, D. (2018). Mixup：超越经验风险最小化. arXiv预印本，arXiv:1710.09412